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Effects of management intervention on post-disturbance community composition: an experimental analysis using bayesian hierarchical models.

ABSTRACT: As human demand for ecosystem products increases, management intervention may become more frequent after environmental disturbances. Evaluations of ecological responses to cumulative effects of management interventions and natural disturbances provide critical decision-support tools for managers who strive to balance environmental conservation and economic development. We conducted an experiment to evaluate the effects of salvage logging on avian community composition in lodgepole pine (Pinus contorta) forests affected by beetle outbreaks in Oregon, USA, 1996-1998. Treatments consisted of the removal of lodgepole pine snags only, and live trees were not harvested. We used a bayesian hierarchical model to quantify occupancy dynamics for 27 breeding species, while accounting for variation in the detection process. We examined how magnitude and precision of treatment effects varied when incorporating prior information from a separate intervention study that occurred in a similar ecological system. Regardless of which prior we evaluated, we found no evidence that the harvest treatment had a negative impact on species richness, with an estimated average of 0.2-2.2 more species in harvested stands than unharvested stands. Estimated average similarity between control and treatment stands ranged from 0.82-0.87 (1 indicating complete similarity between a pair of stands) and suggested that treatment stands did not contain novel assemblies of species responding to the harvesting prescription. Estimated treatment effects were positive for twenty-four (90%) of the species, although the credible intervals contained 0 in all cases. These results suggest that, unlike most post-fire salvage logging prescriptions, selective harvesting after beetle outbreaks may meet multiple management objectives, including the maintenance of avian community richness comparable to what is found in unharvested stands. Our results provide managers with prescription alternatives to respond to severe beetle outbreaks that continue to occur across extensive portions of the dry forests of western North America.

SUBMITTER: Giovanini J

PROVIDER: S-EPMC3606292 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Effects of management intervention on post-disturbance community composition: an experimental analysis using bayesian hierarchical models.

Giovanini Jack J Kroll Andrew J AJ Jones Jay E JE Altman Bob B Arnett Edward B EB

PloS one 20130322 3

As human demand for ecosystem products increases, management intervention may become more frequent after environmental disturbances. Evaluations of ecological responses to cumulative effects of management interventions and natural disturbances provide critical decision-support tools for managers who strive to balance environmental conservation and economic development. We conducted an experiment to evaluate the effects of salvage logging on avian community composition in lodgepole pine (Pinus co ...[more]

PMID: 23533659

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Project description:BackgroundIntegrated community case management (iCCM) involves delivery of simple medicines to children with pneumonia, diarrhea and/or malaria by community health workers (CHWs). Between 2010 and 2012, an iCCM intervention trial was implemented by Healthy Child Uganda. This study used qualitative tools to assess whether project stakeholders perceived that iCCM improved access to care for children under five years of age.MethodsThe intervention involved training and equipping 196 CHWs in 98 study villages in one sub-county in Uganda in iCCM. During the eight-month intervention, CHWs assessed sick children, provided antimalarials (coartem) for fever, antibiotics (amoxicillin) for cough and fast breathing, oral rehydration salts/zinc for diarrhea, and referred very sick children to health facilities. In order to examine community perceptions and acceptability of iCCM, post-intervention focus groups and key respondent interviews involving caregivers, health workers, CHWs and local leaders were carried out by experienced facilitators using semi-structured interview guides. Data were analyzed using thematic analysis techniques.ResultsRespondents reported increased access to health care for children as a result of iCCM. Access was reportedly closer to home, available more hours in a day, and the availability of CHWs was perceived as more reliable. CHW care was reported to be trustworthy and caring. Families reported saving money especially due to reduced transportation costs, and less time away from home. Respondents also perceived better health outcomes. Linkages between health facilities and communities were reportedly improved by the iCCM intervention due to the presence of trained CHWs in the community.ConclusionsiCCM delivered by CHWs may improve access to health care and is acceptable to families. Policymakers should continue to seek opportunities to implement and support iCCM, particularly in remote communities where there are health worker shortages.

Project description:Disease mapping aims to determine the underlying disease risk from scattered epidemiological data and to represent it on a smoothed colored map. This methodology is based on Bayesian inference and is classically dedicated to non-infectious diseases whose incidence is low and whose cases distribution is spatially (and eventually temporally) structured. Over the last decades, disease mapping has received many major improvements to extend its scope of application: integrating the temporal dimension, dealing with missing data, taking into account various a prioris (environmental and population covariates, assumptions concerning the repartition and the evolution of the risk), dealing with overdispersion, etc. We aim to adapt this approach to model rare infectious diseases proposing specific and generic variants of this methodology. In the context of a contagious disease, the outcome of a primary case can in addition generate secondary occurrences of the pathology in a close spatial and temporal neighborhood; this can result in local overdispersion and in higher spatial and temporal dependencies due to direct and/or indirect transmission. In consequence, we test models including a Negative Binomial distribution (instead of the usual Poisson distribution) to deal with local overdispersion. We also use a specific spatio-temporal link in order to better model the stronger spatial and temporal dependencies due to the transmission of the disease. We have proposed and tested 60 Bayesian hierarchical models on 400 simulated datasets and bovine tuberculosis real data. This analysis shows the relevance of the CAR (Conditional AutoRegressive) processes to deal with the structure of the risk. We can also conclude that the negative binomial models outperform the Poisson models with a Gaussian noise to handle overdispersion. In addition our study provided relevant maps which are congruent with the real risk (simulated data) and with the knowledge concerning bovine tuberculosis (real data).

Dataset Information

Effects of management intervention on post-disturbance community composition: an experimental analysis using bayesian hierarchical models.

Publications

Effects of management intervention on post-disturbance community composition: an experimental analysis using bayesian hierarchical models.

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